Keypoint Energy.
SMPLify [1]} estimates camera parameters to leverage 2D keypoint supervision, which may be prone to depth and scale ambiguity. Hence, we develop the keypoint energy on 3D keypoints. For simplicity, we denote \(P_{3D}\)  as \(P\) . \(\mathcal {J}\)  is the joint regressor and \(\mathcal {M}\)  is the parametric model. We formulate the energy term:
